Comparison of alternative extraction methods for secretome profiling in human hepatocellular carcinoma cells

Secreted proteins are important sources for early detection and diagnosis of disease, and as such have received considerable attention. The extraction of low concentration proteins from large volumes of culture media, which are rich in salts and other compounds that interfere with most proteomics techniques, presents a problem for secretome studies. Ultrafiltration, precipitation, and dialysis are three major extraction methods that can be used to overcome this problem. The present study for the first time, compared the merits and shortcomings of these three methods, without bias. Centrifugal ultrafiltration provided the best extraction efficiency, and precipitation provided the highest number of identifiable proteins. The three methods yielded closely related, but different, information on the secretome; thus, they should be considered complementary or, at least, supplementary methods. Three hundred and sixty unique proteins were identified, including 211 potential secreted proteins. Compared with previous studies, this study also identified 42 new secreted proteins. The present study not only offers a reference for the selection of secretome extraction methods, but also expands the secretome database for the investigation of hepatocellular carcinoma.     

Purification and identification of sperm surface proteins and changes during epididymal maturation

Surface membrane proteins have a key role in the sequential interactions between spermatozoa and oocytes. The aim of this study was to characterize protein changes occurring during post-testicular differentiation using a new overall approach to study surface membrane proteins of spermatozoa. A dedicated protocol based on specific purification of surface membrane proteins labeled with sulfo-NHS-SS-biotin was developed for this purpose. Appropriate gel electrophoresis separation and purification methods combined with standard proteomic methods were then used to identify and quantify surface membrane proteins from immature and mature spermatozoa. Membrane-associated proteins were discriminated from integral membrane proteins by differential solubilization. Protein regionalization on the spermatozoon surface was achieved by comparative analysis of the surface protein extracts from the entire spermatozoa and from periacrosomal sperm plasma membranes. Identification of several known proteins and of new proteins related to the process of epididymal maturation showed the reliability of this protocol for specific purification of a subproteome and identification of new sperm membrane proteins. This approach opens up a new area in the search for male fertility markers.     

NClassG+: A classifier for non-classically secreted Gram-positive bacterial proteins

Background  

Most predictive methods currently available for the identification of protein secretion mechanisms have focused on classically secreted proteins. In fact, only two methods have been reported for predicting non-classically secreted proteins of Gram-positive bacteria. This study describes the implementation of a sequence-based classifier, denoted as NClassG+, for identifying non-classically secreted Gram-positive bacterial proteins.     

Rapid purification of bacterially expressed fusion proteins by high-performance liquid chromatography methods

Recent developments in recombinant DNA technology allow the high-level expression in bacteria of substantial amounts of viral and eukaryotic proteins whose genes have been cloned into plasmids. The present study reports two high-performance liquid chromatography (HPLC) methods for the rapid purification to apparent homogeneity of these bacterially expressed proteins. The two methods are anion exchange HPLC in the presence of 7 M Urea and reverse-phase HPLC of protein solubilized by 7.0 M guanidine hydrochloride. The two methods have been used successfully to purify fusion products of the v-myb oncogene and fusion proteins from HTLV-I Px and transmembrane regions and should be of general utility for purification of other bacterially produced proteins.     

Prediction of mitochondrial proteins of malaria parasite using bi-profile Bayes feature extraction

Mitochondrial proteins of Plasmodium falciparum are considered as attractive targets for anti-malarial drugs, but the experimental identification of these proteins is a difficult and time-consuming task. Computational prediction of mitochondrial proteins offers an alternative approach. However, the commonly used subcellular location prediction methods are unsuited for P. falciparum mitochondrial proteins whereas the organism and organelle-specific methods were constructed on the basis of a rather small dataset. In this study, a novel dataset termed PfM233, which included 108 mitochondrial and 125 non-mitochondrial proteins with sequence similarity below 25%, was established and the methods for predicting mitochondrial proteins of P. falciparum were described. Both bi-profile Bayes and split amino acid composition were applied to extract the features from the N- and C-terminal sequences of these proteins, which were then used to construct two SVM based classifiers (PfMP-N25 and PfMP-30). Using PfM233 as the dataset, PfMP-N25 and PfMP-30 achieved accuracies (MCCs) of 90.13% (0.80) and 90.99% (0.82). When tested with the commonly used 40 mitochondrial proteins in PfM175 and the 108 mitochondrial proteins in PfM233, these two methods obviously outperformed the existing general, organelle-specific and organism and organelle-specific methods.     

膜蛋白结晶方法学研究进展

膜蛋白执行着物质运输、能量转换和信号转导等重要生物学功能,其分子的三维结构解析对阐述其功能及开展理性药物设计有着十分重要的意义．目前膜蛋白结构解析以X射线单晶衍射技术为主,该技术需要高质量晶体作为衍射对象．然而由于膜蛋白具有两亲性,难以得到高度有序的三维晶体,进而导致其结构解析十分困难．针对此问题,研究者们发展了一些专门面向膜蛋白的结晶方法,如基于去垢剂的方法,基于脂类的方法等．本文回顾了这些方法,并对未来膜蛋白的结晶研究进行了展望．     

Prediction of functional class of novel plant proteins by a statistical learning method

In plant genomes, the function of a substantial percentage of the putative protein-coding open reading frames (ORFs) is unknown. These ORFs have no significant sequence similarity to known proteins, which complicates the task of functional study of these proteins. Efforts are being made to explore methods that are complementary to, or may be used in combination with, sequence alignment and clustering methods. A web-based protein functional class prediction software, SVMProt, has shown some capability for predicting functional class of distantly related proteins. Here the usefulness of SVMProt for functional study of novel plant proteins is evaluated. To test SVMProt, 49 plant proteins (without a sequence homolog in the Swiss-Prot protein database, not in the SVMProt training set, and with functional indications provided in the literature) were selected from a comprehensive search of MEDLINE abstracts and Swiss-Prot databases in 1999-2004. These represent unique proteins the function of which, at present, cannot be confidently predicted by sequence alignment and clustering methods. The predicted functional class of 31 proteins was consistent, and that of four other proteins was weakly consistent, with published functions. Overall, the functional class of 71.4% of these proteins was consistent, or weakly consistent, with functional indications described in the literature. SVMProt shows a certain level of ability to provide useful hints about the functions of novel plant proteins with no similarity to known proteins.     

Rechecking the Centrality-Lethality Rule in the Scope of Protein Subcellular Localization Interaction Networks

Essential proteins are indispensable for living organisms to maintain life activities and play important roles in the studies of pathology, synthetic biology, and drug design. Therefore, besides experiment methods, many computational methods are proposed to identify essential proteins. Based on the centrality-lethality rule, various centrality methods are employed to predict essential proteins in a Protein-protein Interaction Network (PIN). However, neglecting the temporal and spatial features of protein-protein interactions, the centrality scores calculated by centrality methods are not effective enough for measuring the essentiality of proteins in a PIN. Moreover, many methods, which overfit with the features of essential proteins for one species, may perform poor for other species. In this paper, we demonstrate that the centrality-lethality rule also exists in Protein Subcellular Localization Interaction Networks (PSLINs). To do this, a method based on Localization Specificity for Essential protein Detection (LSED), was proposed, which can be combined with any centrality method for calculating the improved centrality scores by taking into consideration PSLINs in which proteins play their roles. In this study, LSED was combined with eight centrality methods separately to calculate Localization-specific Centrality Scores (LCSs) for proteins based on the PSLINs of four species (Saccharomyces cerevisiae, Homo sapiens, Mus musculus and Drosophila melanogaster). Compared to the proteins with high centrality scores measured from the global PINs, more proteins with high LCSs measured from PSLINs are essential. It indicates that proteins with high LCSs measured from PSLINs are more likely to be essential and the performance of centrality methods can be improved by LSED. Furthermore, LSED provides a wide applicable prediction model to identify essential proteins for different species.     

Osteogenic differentiation of adipose derived stem cells promoted by overexpression of osterix

Secreted proteins, which may be involved in the regulation of various biological processes, are the potential targets for diagnosis and treatment of diverse diseases. In this study, to identify the human hepatoma HepG2 cells-derived secreted proteins more extensively, we applied the protein sample preparations using the combinations of denaturation methods and molecular-mass cutoff via ultrafiltration to the two-dimensional liquid chromatography coupled with tandem mass spectrometry (2D LC–MS/MS) analysis. We were able to identify a total of 86 proteins containing widely known secreted proteins of HepG2 such as alpha-fetoprotein, of which 73 proteins including 27 signal peptide-containing proteins have never been reported to be secreted from HepG2 cells in other proteomic studies. Among the identified signal peptide-containing proteins, ten proteins such as growth differentiation factor 15, osteopontin and stanniocalcin 2 were discovered as new secreted proteins of HepG2 cells. These observations suggest that the combinations of different sample preparation methods and 2D LC–MS/MS analysis are useful for identifying a wider range of low-abundance proteins and that the secreted proteins from HepG2 identified in this study may be useful as liver-specific biomarkers for diagnosis and treatment.     

How to obtain labeled proteins and what to do with them

We review new and established methods for the chemical modification of proteins in living cells and highlight recent applications. The review focuses on tag-mediated protein labeling methods, such as the tetracysteine tag and SNAP-tag, and new developments in this field such as intracellular labeling with lipoic acid ligase. Recent promising advances in the incorporation of unnatural amino acids into proteins are also briefly discussed. We describe new tools using tag-mediated labeling methods including the super-resolution microscopy of tagged proteins, the study of the interactions of proteins and protein domains, the subcellular targeting of synthetic ion sensors, and the generation of new semisynthetic metabolite sensors. We conclude with a view on necessary future developments, with one example being the selective labeling of non-tagged, native proteins in complex protein mixtures.     

Depletion of multiple high-abundance proteins improves protein profiling capacities of human serum and plasma

Systematic detection of low-abundance proteins in human blood that may be putative disease biomarkers is complicated by an extremely wide range of protein abundances. Hence, depletion of major proteins is one potential strategy for enhancing detection sensitivity in serum or plasma. This study compared a recently commercialized HPLC column containing antibodies to six of the most abundant blood proteins ("Top-6 depletion") with either older Cibacron blue/Protein A or G depletion methods or no depletion. In addition, a prototype spin column version of the HPLC column and an alternative prototype two antibody spin column were evaluated. The HPLC polyclonal antibody column and its spin column version are very promising methods for substantially simplifying human serum or plasma samples. These columns show the lowest nonspecific binding of the depletion methods tested. In contrast other affinity methods, particularly dye-based resins, yielded many proteins in the bound fractions in addition to the targeted proteins. Depletion of six abundant proteins removed about 85% of the total protein from human serum or plasma, and this enabled 10- to 20-fold higher amounts of depleted serum or plasma samples to be applied to 2-D gels or alternative protein profiling methods such as protein array pixelation. However, the number of new spots detected on 2-D gels was modest, and most newly visualized spots were minor forms of relatively abundant proteins. The inability to detect low-abundance proteins near expected 2-D staining limits was probably due to both the highly heterogeneous nature of most plasma or serum proteins and masking of many low-abundance proteins by the next series of most abundant proteins. Hence, non2-D methods such as protein array pixelation are more promising strategies for detecting lower abundance proteins after depleting the six abundant proteins.     

Possible target‐related proteins and signal network of bufalin in A549 cells suggested by both iTRAQ‐based and label‐free proteomic analysis

Bufalin (BF) exhibited antiproliferation and antimigration effects on human A549 lung cancer cells. To search its target‐related proteins, protein expression profiles of BF‐treated and control cells were compared using two quantitative proteomic methods, iTRAQ‐based and label‐free proteomic analysis. A total of 5428 proteins were identified in iTRAQ‐based analysis while 6632 proteins were identified in label‐free analysis. The number of common identified proteins of both methods was 4799 proteins. By application of 1.20‐fold for upregulated and 0.83‐fold for downregulated cutoff values, 273 and 802 differentially expressed proteins were found in iTRAQ‐based and label‐free analysis, respectively. The number of common differentially expressed proteins of both methods was 45 proteins. Results of bioinformational analysis using Metacore^TM showed that the two proteomic methods were complementary and both suggested the involvement of oxidative stress and regulation of gene expression in the effects of BF, and fibronectin‐related pathway was suggested to be an important pathway affected by BF. Western blotting assay results confirmed BF‐induced change in levels of fibronectin and other related proteins. Overexpression of fibronectin by plasmid transfection ameliorated antimigration effects of BF. Results of the present study provided information about possible target‐related proteins and signal network of BF.     

Comparison of protein solubilization methods suitable for proteomic analysis of soybean seed proteins

Extraction of soybean seed proteins for two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry analysis is challenging and inconsistent. In this study, we compared four different protein extraction/solubilization methods-urea, thiourea/urea, phenol, and a modified trichloroacetic acid (TCA)/acetone-to determine their efficacy in separating soybean seed proteins by 2D-PAGE. In all four methods, seed storage proteins were well separated by 2D-PAGE with minor variations in the intensity of the spots. The thiourea/urea and TCA methods showed higher protein resolution and spot intensity of all proteins compared with the other two methods. In addition, several less abundant and high molecular weight proteins were clearly resolved and strongly detected using the thiourea/urea and TCA methods. Protein spots obtained from the TCA method were subjected to mass spectrometry analysis to test their quality and compatibility. Fifteen protein spots were selected, digested with trypsin, and analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and liquid chromatography mass spectrometry (LC-MS). The proteins identified were beta-conglycinin, glycinin, Kunitz trypsin inhibitor, alcohol dehydrogenase, Gly m Bd 28K allergen, and sucrose binding proteins. These results suggest that the thiourea/urea and TCA methods are efficient and reliable methods for 2D separation of soybean seed proteins and subsequent identification by mass spectrometry.     

A comparison of X-ray diffraction analysis and nuclear magnetic resonance from the data on the identification of alpha-helices and beta-strands in the same proteins

The methods of X-ray diffraction analysis and nuclear magnetic resonance spectroscopy were compared using the data on the identification of alpha-helices and beta-strands of the same proteins. The goal of the study was to determine whether these identifications can be considered as equivalent in the structural classification of proteins and in the solution of other problems. The identifications obtained by the method of Kabsch and Sander for 56% specially chosen water-soluble proteins were chosen. It was found that the identification of alpha-helices and beta-strands are almost equivalent if used for the structural classification of the proteins. In the analysis of the conformational properties of amino acid residues or their combinations, it is reasonable to use the identifications of alpha-helices and beta-strands, obtained only from the data of X-ray diffraction analysis. An additional outcome of the study is a unique collection of pairs of protein structures obtained by the methods of X-ray diffraction analysis and nuclear magnetic resonance spectroscopy for the same proteins.     

Struggle for photostability: Bleaching mechanisms of fluorescent proteins

In modern biotechnological science, there is a need for visualization of objects under study at the levels of cells, organelles, and individual molecules. Prominent among imaging methods are the methods based on the detection of fluorescence from the fluorophores with which objects under study are labeled. Fluorescent proteins (FPs) are very popular as genetically encoded fluorescent labels for lifetime imaging of target structures and processes in living systems. One of the key characteristics of FPs is their photostability, i.e., their resistance to photochemical reactions that quench the fluorescence signal. This review describes the currently known molecular mechanisms underlying photobleaching and the methods used to improve the photostability of fluorescent proteins.     

New strategies for fluorescently labeling proteins in the study of amyloids

Amyloid proteins are widely studied, both for their unusual biophysical properties and their association with disorders such as Alzheimer’s and Parkinson’s disease. Fluorescence-based methods using site-specifically labeled proteins can provide information on the details of their structural dynamics and their roles in specific biological processes. Here, we describe the application of different labeling methods and novel fluorescent probe strategies to the study of amyloid proteins, both for in vitro biophysical experiments and for in vivo imaging. These labeling tools can be elegantly used to answer important questions on the function and pathology of amyloid proteins.     

High-throughput identification of purification conditions leads to preliminary crystallization conditions for three inner membrane proteins

An important factor in the crystallization, and subsequent structural determination, of integral membrane proteins is the ability to produce a stable and monodisperse solution of the protein. Obtaining the correct purification detergent to achieve this can be laborious and is often serendipitous. In this study, high-throughput methods are used to analyze the suitability of eight different detergents on the stability of 12 inner transmembrane proteins from Escherichia coli. The best results obtained from the small-scale experiments were scaled up, the aggregation state of the proteins assessed, and all monodisperse protein solutions entered into crystallization trials. This resulted in preliminary crystallization hits for three inner membrane proteins: XylH, PgpB and YjdL and this study reports the methods, purification procedures and crystallization conditions used to achieve this.     

Evaluation of three principally different intact protein prefractionation methods for plasma biomarker discovery

The aim of this study was to evaluate three principally different top-down protein prefractionation methods for plasma: high-abundance protein depletion, size fractionation and peptide ligand affinity beads, focusing in particular on compatibility with downstream analysis, reproducibility and analytical depth. Our data clearly demonstrates the benefit of high-abundance protein depletion. However, MS/MS analysis of the proteins eluted from the high-abundance protein depletion column show that more proteins than aimed for are removed and, in addition, that the depletion efficacy varies between the different high-abundance proteins. Although a smaller number of proteins were identified per fraction using the peptide ligand affinity beads, this technique showed to be both robust and versatile. Size fractionation, as performed in this study, focusing on the low molecular weight proteome using a combination of gel filtration chromatography and molecular weight cutoff filters, showed limitations in the molecular weight cutoff precision leading detection of high molecular weight proteins and, in the case of the cutoff filters, high variability. GeLC-MS/MS analysis of the fractionation methods in combination with pathway analysis demonstrates that increased fractionation primarily leads to high proteome coverage of pathways related to biological functions of plasma, such as acute phase reaction, complement cascade and coagulation. Further, the prefractionation methods in this study induces limited effect on the proportion of tissue proteins detected, thereby highlighting the importance of extensive or targeted downstream fractionation.     

Structure determination of membrane proteins in five easy pieces

Rotational Alignment (RA) solid-state NMR provides the basis for a general method for determining the structures of membrane proteins in phospholipid bilayers under physiological conditions. Membrane proteins are high priority targets for structure determination, and are challenging for existing experimental methods. Because membrane proteins reside in liquid crystalline phospholipid bilayer membranes it is important to study them in this type of environment. The RA solid-state NMR approach we have developed can be summarized in five steps, and incorporates methods of molecular biology, biochemistry, sample preparation, the implementation of NMR experiments, and structure calculations. It relies on solid-state NMR spectroscopy to obtain high-resolution spectra and residue-specific structural restraints for membrane proteins that undergo rotational diffusion around the membrane normal, but whose mobility is otherwise restricted by interactions with the membrane phospholipids. High resolution spectra of membrane proteins alone and in complex with other proteins and ligands set the stage for structure determination and functional studies of these proteins in their native, functional environment.     

Facile detection of protein-protein interactions by one-dimensional NMR spectroscopy

Two methods for detecting protein-protein interactions in solution using one-dimensional (1D) NMR spectroscopy are described. Both methods rely on measurement of the intensity of the strongest methyl resonance (SMR), which for most proteins is observed at 0.8-0.9 ppm. The severe resonance overlap in this region facilitates detection of the SMR at low micromolar and even sub-micromolar protein concentrations. A decreased SMR intensity in the 1H NMR spectrum of a protein mixture compared to the added SMR intensities of the isolated proteins reports that the proteins interact (SMR method). Decreased SMR intensities in 1D 13C-edited 1H NMR spectra of 13C-labeled proteins upon addition of unlabeled proteins or macromolecules also demonstrate binding (SMRC method). Analysis of the interaction between XIAP and Smac, two proteins involved in apoptosis, illustrates both methods. A study showing that phospholipids compete with the neuronal core complex for Ca2+-dependent binding to the presynaptic Ca2+-sensor synaptotagmin 1 illustrates the usefulness of the SMRC method in studying multicomponent systems.